Omics Multi-Layers Networks Provide Novel Mechanistic and Functional Insights Into Fat Storage and Lipid Metabolism in Poultry

Fatty acid metabolism in poultry has a major impact on production and disease resistance traits. According to the high rate of interactions between lipid metabolism and its regulating properties, a holistic approach is necessary. To study omics multilayers of adipose tissue and identification of genes and miRNAs involved in fat metabolism, storage and endocrine signaling pathways in two groups of broiler chickens with high and low abdominal fat, as well as high-throughput techniques, were used. The gene–miRNA interacting bipartite and metabolic-signaling networks were reconstructed using their interactions. In the analysis of microarray and RNA-Seq data, 1,835 genes were detected by comparing the identified genes with significant expression differences (p.adjust < 0.01, fold change ≥ 2 and ≤ −2). Then, by comparing between different data sets, 34 genes and 19 miRNAs were detected as common and main nodes. A literature mining approach was used, and seven genes were identified and added to the common gene set. Module finding revealed three important and functional modules, which were involved in the peroxisome proliferator-activated receptor (PPAR) signaling pathway, biosynthesis of unsaturated fatty acids, Alzheimer’s disease metabolic pathway, adipocytokine, insulin, PI3K–Akt, mTOR, and AMPK signaling pathway. This approach revealed a new insight to better understand the biological processes associated with adipose tissue

Integrated Network Analysis to Identify Key Modules and Potential Hub Genes Involved in Bovine Respiratory Disease: A Systems Biology Approach

Background: Bovine respiratory disease (BRD) is the most common disease in the beef and dairy cattle industry. BRD is a multifactorial disease resulting from the interaction between environmental stressors and infectious agents. However, the molecular mechanisms underlying BRD are not fully understood yet. Therefore, this study aimed to use a systems biology approach to systematically evaluate this disorder to better understand the molecular mechanisms responsible for BRD. Methods: Previously published RNA-seq data from whole blood of 18 healthy and 25 BRD samples were downloaded from the Gene Expression Omnibus (GEO) and then analyzed. Next, two distinct methods of weighted gene coexpression network analysis (WGCNA), i.e., module–trait relationships (MTRs) and module preservation (MP) analysis were used to identify significant highly correlated modules with clinical traits of BRD and non-preserved modules between healthy and BRD samples, respectively. After identifying respective modules by the two mentioned methods of WGCNA, functional enrichment analysis was performed to extract the modules that are biologically related to BRD. Gene coexpression networks based on the hub genes from the candidate modules were then integrated with protein–protein interaction (PPI) networks to identify hub–hub genes and potential transcription factors (TFs). Results: Four significant highly correlated modules with clinical traits of BRD as well as 29 non-preserved modules were identified by MTRs and MP methods, respectively. Among them, two significant highly correlated modules (identified by MTRs) and six nonpreserved modules (identified by MP) were biologically associated with immune response, pulmonary inflammation, and pathogenesis of BRD. After aggregation of gene coexpression networks based on the hub genes with PPI networks, a total of 307 hub–hub genes were identified in the eight candidate modules. Interestingly, most of these hub–hub genes were reported to play an important role in the immune response and BRD pathogenesis. Among the eight candidate modules, the turquoise (identified by MTRs) and purple (identified by MP) modules were highly biologically enriched in BRD. Moreover, STAT1, STAT2, STAT3, IRF7, and IRF9 TFs were suggested to play an important role in the immune system during BRD by regulating the coexpressed genes of these modules. Additionally, a gene set containing several hub–hub genes was identified in the eight candidate modules, such as TLR2, TLR4, IL10, SOCS3, GZMB, ANXA1, ANXA5, PTEN, SGK1, IFI6, ISG15, MX1, MX2, OAS2, IFIH1, DDX58, DHX58, RSAD2, IFI44, IFI44L, EIF2AK2, ISG20, IFIT5, IFITM3, OAS1Y, HERC5, and PRF1, which are potentially critical during infection with agents of bovine respiratory disease complex (BRDC). Conclusion: This study not only helps us to better understand the molecular mechanisms responsible for BRD but also suggested eight candidate modules along with several promising hub–hub genes as diagnosis biomarkers and therapeutic targets for BRD

Feasibility study for application of the marine coral powder as an adsorbent for Volatile Organic Hydrocarbons

The marine coral has a porous outer surface and it has served in the processes such as water treatment systems, removal of carbon dioxide and adsorption of arsenic. Based on the need for cheap and efficient adsorbents, in sampling, the aim of this study, comparison of the efficiency of marine coral powder and activated charcoal in adsorption of volatile organic hydrocarbons was considered. In this experimental research, a certain concentrations of 8 volatile organic hydrocarbons: (para-Xylene, Chloroform, Carbon tetrachloride, tert-Butanol, Pyridine, Acetone, Ethyl acetate and Diethyl ether) was injected into dynamic atmospheric chamber in the NTP (Normal Temperature and Pressure) conditions. Air sampling was performed with the tube containing marine coral powder as well as the tube of activated charcoal, based on the standard method of NIOSH (National Institute of Occupational Safety and Health) and in the same laboratory conditions. Then samples were injected into the gas Chromatograph apparatus and analytical comparison has been done between the amount of adsorption of hydrocarbons by activated charcoal and coral powder-test and Mann-Whitney were done with SPSS V.20.Findings showed that there was a significant difference between the amount of adsorption of Para-Xylene, carbon tetrachloride, tert-Butanol, Pyridine, acetone and Ethyl acetate hydrocarbons by activated charcoal and coral powder (

Diagnostic value of NIPT assay for fetal aneuploidy screening in pregnant women with moderate risk of trisomy in first stage screening

Introduction: Aneuploidies are of the most important fetal abnormalities. Diagnostic value and efficacy of NIPT assay in the groups with abnormal results for first trimester combined screening test is not well defined. Therefore, this study was performed aimed to survey the sensitivity and specificity of NIPT for aneuploidies diagnosis in women with moderate risk for trisomy at first trimester combined screening test. Methods: This prospective cohort study was performed in 2017-2018 on 447 women with singleton pregnancy and gestational age of 11 to 13 weeks and 6 days who had moderate risk for trisomy. NIPT analysis was done in all women with moderate risk (1/250 to 1/1500) and was compared with the results from karyotype and phenotype analysis in neonates. NIPT diagnostic accuracy for chromosomal abnormalities was calculated. Data were analyzed using SPSS statistical software (version 22). Results: Two cases with trisomy 21 (0.06%) and one case with trisomy 18 (0.03%) were diagnosed. These three cases were confirmed with amniocentesis and the pregnancy was ended. The neonates' analysis showed normal phenotype results in all of them and NIPT diagnostic accuracy for trisomy 21 and 18 was calculated 100%. Conclusion: In addition to maintain combined screening test benefits, using NIPT is accompanied by high diagnostic accuracy for fetal chromosomal abnormalities assessment

Construction of a circRNA– lincRNA–lncRNA–miRNA–mRNA ceRNA regulatory network identifies genes and pathways linked to goat fertility

Background: There is growing interest in the genetic improvement of fertility traits in female goats. With high-throughput genotyping, single-cell RNA sequencing (scRNA-seq) is a powerful tool for measuring gene expression profiles. The primary objective was to investigate comparative transcriptome profiling of granulosa cells (GCs) of high- and low-fertility goats, using scRNA-seq.Methods: Thirty samples from Ji’ning Gray goats (n = 15 for high fertility and n = 15 for low fertility) were retrieved from publicly available scRNA-seq data. Functional enrichment analysis and a literature mining approach were applied to explore modules and hub genes related to fertility. Then, interactions between types of RNAs identified were predicted, and the ceRNA regulatory network was constructed by integrating these interactions with other gene regulatory networks (GRNs).Results and discussion: Comparative transcriptomics-related analyses identified 150 differentially expressed genes (DEGs) between high- and low-fertility groups, based on the fold change (≥5 and ≤−5) and false discovery rate (FDR &lt;0.05). Among these genes, 80 were upregulated and 70 were downregulated. In addition, 81 mRNAs, 58 circRNAs, 8 lincRNAs, 19 lncRNAs, and 55 miRNAs were identified by literature mining. Furthermore, we identified 18 hub genes (SMAD1, SMAD2, SMAD3, SMAD4, TIMP1, ERBB2, BMP15, TGFB1, MAPK3, CTNNB1, BMPR2, AMHR2, TGFBR2, BMP4, ESR1, BMPR1B, AR, and TGFB2) involved in goat fertility. Identified biological networks and modules were mainly associated with ovary signature pathways. In addition, KEGG enrichment analysis identified regulating pluripotency of stem cells, cytokine–cytokine receptor interactions, ovarian steroidogenesis, oocyte meiosis, progesterone-mediated oocyte maturation, parathyroid and growth hormone synthesis, cortisol synthesis and secretion, and signaling pathways for prolactin, TGF-beta, Hippo, MAPK, PI3K-Akt, and FoxO. Functional annotation of identified DEGs implicated important biological pathways. These findings provided insights into the genetic basis of fertility in female goats and are an impetus to elucidate molecular ceRNA regulatory networks and functions of DEGs underlying ovarian follicular development

Differential Co-Expression Network Analysis Reveals Key Hub-High Traffic Genes as Potential Therapeutic Targets for COVID-19 Pandemic

BackgroundThe recent emergence of COVID-19, rapid worldwide spread, and incomplete knowledge of molecular mechanisms underlying SARS-CoV-2 infection have limited development of therapeutic strategies. Our objective was to systematically investigate molecular regulatory mechanisms of COVID-19, using a combination of high throughput RNA-sequencing-based transcriptomics and systems biology approaches. MethodsRNA-Seq data from peripheral blood mononuclear cells (PSPRINGER NATUREs) of healthy persons, mild and severe 17 COVID-19 patients were analyzed to generate a gene expression matrix. Weighted gene co-expression network analysis (WGCNA) was used to identify co-expression modules in healthy samples as a reference set. For differential co-expression network analysis, module preservation and module-trait relationships approaches were used to identify key modules. Then, protein-protein interaction (PPI) networks, based on co-expressed hub genes, were constructed to identify hub genes/TFs with the highest information transfer (hub-high traffic genes) within candidate modules. ResultsBased on differential co-expression network analysis, connectivity patterns and network density, 72% (15 of 21) of modules identified in healthy samples were altered by SARS-CoV-2 infection. Therefore, SARS-CoV-2 caused systemic perturbations in host biological gene networks. In functional enrichment analysis, among 15 non-preserved modules and two significant highly-correlated modules (identified by MTRs), 9 modules were directly related to the host immune response and COVID-19 immunopathogenesis. Intriguingly, systemic investigation of SARS-CoV-2 infection identified signaling pathways and key genes/proteins associated with COVID-19's main hallmarks, e.g., cytokine storm, respiratory distress syndrome (ARDS), acute lung injury (ALI), lymphopenia, coagulation disorders, thrombosis, and pregnancy complications, as well as comorbidities associated with COVID-19, e.g., asthma, diabetic complications, cardiovascular diseases (CVDs), liver disorders and acute kidney injury (AKI). Topological analysis with betweenness centrality (BC) identified 290 hub-high traffic genes, central in both co-expression and PPI networks. We also identified several transcriptional regulatory factors, including NFKB1, HIF1A, AHR, and TP53, with important immunoregulatory roles in SARS-CoV-2 infection. Moreover, several hub-high traffic genes, including IL6, IL1B, IL10, TNF, SOCS1, SOCS3, ICAM1, PTEN, RHOA, GDI2, SUMO1, CASP1, IRAK3, HSPA5, ADRB2, PRF1, GZMB, OASL, CCL5, HSP90AA1, HSPD1, IFNG, MAPK1, RAB5A, and TNFRSF1A had the highest rates of information transfer in 9 candidate modules and central roles in COVID-19 immunopathogenesis. ConclusionThis study provides comprehensive information on molecular mechanisms of SARS-CoV-2-host interactions and identifies several hub-high traffic genes as promising therapeutic targets for the COVID-19 pandemic

Epidemiological Characterization of Drug Resistance among Mycobacterium tuberculosis Isolated from Patients in Northeast of Iran during 2012-2013

Introduction. Tuberculosis is still one of the most important health problems in developing countries and increasing drug resistance is the main concern for its treatment. This study was designed to characterize the drug resistant Mycobacterium tuberculosis isolated from patients suffering from pulmonary tuberculosis in northeast of Iran. Method. In this cross-sectional study during 2012-2013, drug susceptibility testing was performed on Mycobacterium tuberculosis isolated in northeast of Iran using proportional method. Epidemiological data concerning these strains were also analyzed. Results. Among 125 studied isolates, 25 mycobacteria (20%) were diagnosed as nontuberculosis mycobacteria. Among the remaining 100 Mycobacterium tuberculosis isolates, the resistance rates were 7%, 7%, 3%, and 9% against isoniazid, rifampin, ethambutol, and streptomycin, respectively. Four isolates were resistant against both isoniazid and rifampin (MDR tuberculosis). The highest resistance rate was observed among 15-45-year-old patients. The MDR tuberculosis was much more prevalent among those who had previous history of treatment. Conclusion. Considering these findings, DOTS strategy should be emphasized and promptly used in order to prevent further resistance. Regarding the high rate of nontuberculosis mycobacteria, it is recommended that confirmatory tests were performed before any therapeutic decision

In vivo effects of allogeneic mesenchymal stem cells in a rat model of acute ischemic kidney injury

Objective(s): Renal ischemia-reperfusion injury (IRI) as a severe condition of acute kidney injury (AKI) is the most common clinical problem with high mortality rates of 35-60% deaths in hospital. Mesenchymal stem cells (MSC) due to unique regenerative characteristics are ideal candidates for the treatment of the ischemic injuries. This work is focused on the administration of MSC to IRI-induced AKI Wistar rats and evaluating their significance in AKI treatment. Material and Methods: Animals underwent surgical procedure and AKI was induced by 40 min bilateral renal pedicle clamping. Immediately after reperfusion, 2×106 rat bone marrow derived MSCs were injected via intra-parenchymal or intra-aortic route. Results: Animals subjected to AKI after days 1 and 3 showed significant increase in the serum creatinine and blood urea nitrogen (BUN) concentration along with a declined glomerular filtration rate (GFR) when compared with non-ischemic animals. On the other hand, treated animals showed a significant enhanced regeneration as compared to ischemic animals in both administration route groups. Conclusion: According to the results concluded from the renoprotective effects of MSC in IRI/AKI, MSCs could be considered as promising therapeutic approach for AKI in clinical applications

A Mendelian Randomization Analysis Investigates Causal Associations between Inflammatory Bowel Diseases and Variable Risk Factors

The question of whether variable risk factors and various nutrients are causally related to inflammatory bowel diseases (IBDs) has remained unanswered so far. Thus, this study investigated whether genetically predicted risk factors and nutrients play a function in the occurrence of inflammatory bowel diseases, including ulcerative colitis (UC), non-infective colitis (NIC), and Crohn’s disease (CD), using Mendelian randomization (MR) analysis. Utilizing the data of genome-wide association studies (GWASs) with 37 exposure factors, we ran Mendelian randomization analyses based on up to 458,109 participants. Univariable and multivariable MR analyses were conducted to determine causal risk factors for IBD diseases. Genetic predisposition to smoking and appendectomy as well as vegetable and fruit intake, breastfeeding, n-3 PUFAs, n-6 PUFAs, vitamin D, total cholesterol, whole-body fat mass, and physical activity were related to the risk of UC (p < 0.05). The effect of lifestyle behaviors on UC was attenuated after correcting for appendectomy. Genetically driven smoking, alcohol consumption, appendectomy, tonsillectomy, blood calcium, tea intake, autoimmune diseases, type 2 diabetes, cesarean delivery, vitamin D deficiency, and antibiotic exposure increased the risk of CD (p < 0.05), while vegetable and fruit intake, breastfeeding, physical activity, blood zinc, and n-3 PUFAs decreased the risk of CD (p < 0.05). Appendectomy, antibiotics, physical activity, blood zinc, n-3 PUFAs, and vegetable fruit intake remained significant predictors in multivariable MR (p < 0.05). Besides smoking, breastfeeding, alcoholic drinks, vegetable and fruit intake, vitamin D, appendectomy, and n-3 PUFAs were associated with NIC (p < 0.05). Smoking, alcoholic drinks, vegetable and fruit intake, vitamin D, appendectomy, and n-3 PUFAs remained significant predictors in multivariable MR (p < 0.05). Our results provide new and comprehensive evidence demonstrating that there are approving causal effects of various risk factors on IBDs. These findings also supply some suggestions for the treatment and prevention of these diseases

Identification of novel candidate targets for suppressing ovarian cancer progression through IL-33/ST2 axis components using the system biology approach

Background: Cancer-associated fibroblasts (CAFs) of ovarian cancer (OvC) are the most prevalent element of the tumor microenvironment (TM). By promoting angiogenesis, immunological suppression, and invasion, CAFs speed up the growth of tumors by changing the extracellular matrix’s structure and composition and/or initiating the epithelial cells (EPT). IL-33/ST2 signaling has drawn a lot of attention since it acts as a pro-tumor alarmin and encourages spread by altering TM.Methods: Differentially expressed genes (DEGs) of the OvC tumor microenvironment were found in the GEO database, qRT-PCR, western blotting, and immunohistochemistry, and their presence and changes in healthy and tumor tissue content were examined. Primary cultures of healthy fibroblasts and CAFs obtained from healthy and tumor tissues retrieved from OvC samples were used for in vitro and in vivo investigations. Cultured primary human CAFs were utilized to investigate the regulation and the IL-33/ST2 axis role in the inflammation reactions.Results: Although ST2 and IL-33 expression was detected in both epithelial (EPT) and fibroblast cells of ovarian cancer, they are more abundant in CAFs. Lipopolysaccharides, serum amyloid A1, and IL-1β, the inflammatory mediators, could all induce IL-33 expression through NF-κB activation in human CAFs. In turn, via the ST2 receptor, IL-33 affected the production of IL-6, IL-1β, and PTGS2 in human CAFs via the MAPKs-NF-κB pathway.Conclusion: Our findings suggest that IL-33/ST2 is affected by the interaction of CAFs and epithelial cells inside the tumor microenvironment. Activation of this axis leads to increased expression of inflammatory factors in tumor CAFs and EPT cells. Therefore, targeting the IL-33/ST2 axis could have potential value in the prevention of OvC progression